Using reference traces for validation of communication in embedded systems

This paper addresses the problem of evaluating the communication behavior of embedded systems. An important problem is missing, wrong or incomplete specification for the interaction in the distributed system. In this paper, a new approach for evaluating the communication behavior based on reference traces is introduced. The benefit of the approach is that it works automatically, with low additional effort and without using any specification. The introduced methodology uses algorithms from the field of machine learning to extract behavior models out of a reference trace. With the presented algorithm, the complexity of the learning problem can be reduced significantly by identifying parallel execution paths. The efficiency of the proposed algorithm is evaluated with real vehicle network data. At this data the self-learning algorithm covers up to 69% of the behavior from the presented trace.